A Threshold Stochastic Conditional Duration Model for Financial Transaction Data

Posted: 31 Mar 2013 Last revised: 1 Jan 2015

See all articles by Zhongxian Men

Zhongxian Men

Independent

Tony S. Wirjanto

University of Waterloo - School of Accounting and Finance; University of Waterloo, Department of Statistics & Actuarial Science

Adam Kolkiewicz

Independent

Date Written: December 31, 2014

Abstract

This paper proposes a threshold stochastic conditional duration (TSCD) model to capture the asymmetric property of financial transactions. The innovation of the observable duration equation is assumed to follow a threshold distribution with two component distributions switching between two regimes. The distributions in different regimes are assumed to be Exponential, Gamma or Weibull. To account for uncertainty in the unobserved threshold level, the observed durations are treated as self-exciting threshold variables. Adopting a Bayesian approach, we develop novel Markov Chain Monte Carlo algorithms to estimate all of the unknown parameters and latent states. To forecast the one-step ahead durations, we employ an auxiliary particle filter where the filter and prediction distributions of the latent states are approximated. The proposed model and the developed MCMC algorithms are illustrated by using both simulated and actual financial transaction data. For model selection, a Bayesian deviance information criterion is calculated to compare our model with other competing models in the literature. Overall, we find that the threshold SCD model performs better than the SCD model when a single positive distribution is assumed for the innovation of the duration equation.

Keywords: Threshold, MCMC, Auxiliary particle filter, Deviance information criterion

JEL Classification: C10, C11, C41, G10

Suggested Citation

Men, Zhongxian and Wirjanto, Tony S. and Kolkiewicz, Adam, A Threshold Stochastic Conditional Duration Model for Financial Transaction Data (December 31, 2014). Available at SSRN: https://ssrn.com/abstract=2241190

Zhongxian Men

Independent ( email )

Tony S. Wirjanto (Contact Author)

University of Waterloo - School of Accounting and Finance ( email )

200 University Avenue West
Waterloo, Ontario N2L 3G1
Canada
519-888-4567 x35210 (Phone)

HOME PAGE: http://https://uwaterloo.ca/statistics-and-actuarial-science/people-profiles/tony-wirjanto

University of Waterloo, Department of Statistics & Actuarial Science ( email )

200 University Avenue West
Waterloo, Ontario N2L 3G1
Canada
519-888-4567 x35210 (Phone)
519-746-1875 (Fax)

HOME PAGE: http://math.uwaterloo.ca/statistics-and-actuarial-science/people-profiles/tony-wirjanto

Adam Kolkiewicz

Independent ( email )

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